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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
PAB 93
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This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
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What Stands Out
Detalles de producto
| Publisher | O'Reilly Media |
| Publication date | 31 Oct. 2022 |
| Edition | 3rd |
| Language | English |
| Print length | 861 pages |
| ISBN-10 | 1098125975 |
| ISBN-13 | 978-1098125974 |
| Item weight | 1.36 kg |
| Dimensions | 18.42 x 5.08 x 24.13 cm |
Who Should Buy?
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Beginner Learners
Newcomers to machine learning who want a comprehensive introduction with practical examples and clear explanations will benefit greatly.
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Data Scientists
Professionals looking to enhance their practical skills in building machine learning models using popular libraries like TensorFlow and Keras.
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Computer Science Students
University students studying machine learning concepts who need a resourceful guide with hands-on coding exercises and projects.
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Advanced Practitioners
Experienced data scientists may find the content too basic and lacking in depth for their advanced needs.
DESCRIPCIÓN DEL PRODUCTO
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
Preguntas y respuestas de los clientes
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Pregunta:
What programming language is used in this book?
Respuesta: The book uses Python programming language with Scikit-learn, Keras, and TensorFlow frameworks. -
Pregunta:
Do I need prior experience in deep learning?
Respuesta: No, the book is suitable for programmers with little to no prior experience in deep learning. -
Pregunta:
Does the book cover unsupervised learning techniques?
Respuesta: Yes, the book covers unsupervised learning techniques such as clustering, dimensionality reduction, and anomaly detection.
AI & Machine Learning Editorial Review
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PAB 93
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características y beneficios
- Book explores machine learning techniques using Scikit-learn, Keras and TensorFlow
- Suitable for programmers with no prior experience in deep learning
- Covers a range of models from simple linear regression to deep neural networks
- Includes code examples and exercises throughout the book
- Dives into neural net architectures for computer vision, NLP, generative models, deep reinforcement learning
- Explores unsupervised learning techniques like clustering, dimensionality reduction and anomaly detection
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